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Volume 41 Issue 7
Jul.  2019
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Changyu HU, Ling WANG, Dongqiang ZHU. Sparse ISAR Imaging Exploiting Dictionary Learning[J]. Journal of Electronics & Information Technology, 2019, 41(7): 1735-1742. doi: 10.11999/JEIT180747
Citation: Changyu HU, Ling WANG, Dongqiang ZHU. Sparse ISAR Imaging Exploiting Dictionary Learning[J]. Journal of Electronics & Information Technology, 2019, 41(7): 1735-1742. doi: 10.11999/JEIT180747

Sparse ISAR Imaging Exploiting Dictionary Learning

doi: 10.11999/JEIT180747
Funds:  The National Natural Science Foundation of China (61871217), The Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX18_0291)
  • Received Date: 2018-07-23
  • Rev Recd Date: 2019-01-21
  • Available Online: 2019-02-14
  • Publish Date: 2019-07-01
  • In view of the imaging quality of sparse ISAR imaging methods is limited by the inaccurate sparse representation of the scene to be imaged, the Dictionary Learning (DL) technique is introduced into ISAR sparse imaging to get better sparse representation of the scene. An off-line DL based imaging method and an on-line DL based imaging method are proposed. The off-line DL imaging method can obtain a better sparse representation via a dictionary learned from the available ISAR images. The on-line DL imaging method can obtain the sparse representation from the data currently considered by jointly optimizing the imaging and DL processes. The results of both simulated and real ISAR data show that the on-line DL imaging method and the off-line dictionary imaging method are both able to better sparsely represent the target scene leading to better imaging results. The off-line DL based imaging method works better than the on-line DL based imaging method with respect to both imaging quality and computational efficiency.
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  • PRICKETT M J and CHEN C C. Principles of inverse synthetic aperture radar /ISAR/ imaging[C]. IEEE Electronics and Aerospace Systems Conference, New York, USA, 1980: 340–345.
    GENG Minming, TIAN Ye, FANG Jian, et al. Implementation of GPU-based iterative shrinkage-thresholding algorithm in sparse microwave imaging[C]. Proceedings of 2012 IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany, 2012: 3863–3866.
    CETIN M and KARL W C. Feature-enhanced synthetic aperture radar image formation based on nonquadratic regularization[J]. IEEE Transactions on Image Processing, 2001, 10(4): 623–631. doi: 10.1109/83.913596
    汪玲, 朱栋强, 马凯莉, 等. 空间目标卡尔曼滤波稀疏成像方法[J]. 电子与信息学报, 2018, 40(4): 846–852. doi: 10.11999/JEIT170319

    WANG Ling, ZHU Dongqiang, MA Kaili, et al. Sparse imaging of space targets using Kalman filter[J]. Journal of Electronics &Information Technology, 2018, 40(4): 846–852. doi: 10.11999/JEIT170319
    徐宗本, 吴一戎, 张冰尘, 等. 基于L1/2正则化理论的稀疏雷达成像[J]. 科学通报, 2018, 63(14): 1306–1319. doi: 10.1360/N972018-00372

    XU Zongben, WU Yirong, ZHANG Bingchen, et al. Sparse radar imaging based on L1/2 regularization theory[J]. Chinese Science Bulletin, 2018, 63(14): 1306–1319. doi: 10.1360/N972018-00372
    HASANKHAN M J, SAMADI S, and ÇETIN M. Sparse representation-based algorithm for joint SAR image formation and autofocus[J]. Signal, Image and Video Processing, 2017, 11(4): 589–596. doi: 10.1007/s11760-016-0998-y
    BI Hui, BI Guoan, ZHANG Bingchen, et al. Complex-image-based sparse SAR imaging and its equivalence[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(9): 5006–5014. doi: 10.1109/TGRS.2018.2803802
    SAMADI S, CETIN M, and MASNADI-SHIRAZI M A. Sparse representation-based synthetic aperture radar imaging[J]. IET Radar, Sonar & Navigation, 2011, 5(2): 182–193. doi: 10.1049/iet-rsn.2009.0235
    WANG Ling, LOFFELD O, MA Kaili, et al. Sparse ISAR imaging using a greedy kalman filtering approach[J]. Signal Processing, 2017, 138: 1–10. doi: 10.1016/j.sigpro.2017.03.002
    DONOHO D L. Compressed sensing[J]. IEEE Transactions on Information Theory, 2006, 52(4): 1289–1306. doi: 10.1109/TIT.2006.871582
    BARANIUK R and STEEGHS P. Compressive radar imaging[C]. Proceedings of 2007 IEEE Radar Conference, Boston, USA, 2007: 128–133.
    WANG Lu, ZHAO Lifan, and BI Guoan. Structured sparse representation based ISAR imaging[C]. Proceedings of the 2014 15th International Radar Symposium, Gdansk, Poland, 2014: 1–5.
    YANKELEVSKY Y and ELAD M. Dictionary learning for high dimensional graph signals[C]. Proceedings of 2018 IEEE International Conference on Acoustics, Speech and Signal Processing, Calgary, Canada, 2018: 4669–4673.
    YANKELEVSKY Y and ELAD M. Structure-aware classification using supervised dictionary learning[C]. Proceedings of 2017 IEEE International Conference on Acoustics, Speech and Signal Processing, New Orleans, USA, 2017: 4421–4425.
    SOĞANLUI A and ÇETIN M. Dictionary learning for sparsity-driven SAR image reconstruction[C]. Proceedings of 2014 IEEE International Conference on Image Processing, Paris, France, 2014: 1693–1697.
    JIANG Changhui, ZHANG Qiyang, FAN Rui, et al. Super-resolution CT image reconstruction based on dictionary learning and sparse representation[J]. Scientific Reports, 2018, 8(1): 8799. doi: 10.1038/s41598-018-27261-z
    AHARON M, ELAD M, and BRUCKSTEIN A. rmK-SVD: An algorithm for designing overcomplete dictionaries for sparse representation[J]. IEEE Transactions on Signal Processing, 2006, 54(11): 4311–4322. doi: 10.1109/TSP.2006.881199
    PATI Y C, REZAIIFAR R, and KRISHNAPRASAD P S. Orthogonal matching pursuit: recursive function approximation with applications to wavelet decomposition[C]. Proceedings of the 27th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, USA, 1993: 40–44.
    WANG Ling and LOFFELD O. ISAR imaging using a null space ℓ1minimizing Kalman filter approach[C]. Proceedings of the 2016 4th International Workshop on Compressed Sensing Theory and Its Applications to Radar, Sonar and Remote Sensing, Aachen, Germany, 2016: 232–236.
    AHARON M and ELAD M. Sparse and redundant modeling of image content using an image-signature-dictionary[J]. SIAM Journal on Imaging Sciences, 2008, 1(3): 228–247. doi: 10.1137/07070156X
    ZHU Daiyin, WANG Ling, YU Yusheng, et al. Robust ISAR range alignment via minimizing the entropy of the average range profile[J]. IEEE Geoscience and Remote Sensing Letters, 2009, 6(2): 204–208. doi: 10.1109/LGRS.2008.2010562
    汪玲, 朱岱寅, 朱兆达. 基于SAR实测数据的舰船成像研究[J]. 电子与信息学报, 2007, 29(2): 401–404.

    WANG Ling, ZHU Daiyin, and ZHU Zhaoda. Study on ship imaging using SAR real data[J]. Journal of Electronics &Information Technology, 2007, 29(2): 401–404.
    HU Changyu, WANG Ling, and LOFFELD O. Inverse synthetic aperture radar imaging exploiting dictionary learning[C]. Proceedings of 2018 IEEE Radar Conference, Oklahoma City, USA, 2018: 1084–1088.
    LOFFELD O, ESPETER T, and CONDE M H. From weighted least squares estimation to sparse CS reconstruction[C]. Proceedings of the 2015 3rd International Workshop on Compressed Sensing Theory and Its Applications to Radar, Sonar and Remote Sensing, Pisa, Italy, 2015: 149–153.
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